ggplot + plotly

## AN INTRO TO GGPLOT + PLOTLY TUTORIALS 

# INSTALL PACKAGES

library(ggplot2)
library(plotly)

## 
## Attaching package: 'plotly'

## The following object is masked from 'package:ggplot2':
## 
##     last_plot

## The following object is masked from 'package:stats':
## 
##     filter

## The following object is masked from 'package:graphics':
## 
##     layout

# CREATE A BASIC GGPLOT2 PLOT

p <- ggplot(mtcars, aes(x = wt, y = mpg)) +
  geom_point() +
  labs(title = "Car Weight vs. MPG",
       x = "Weight (1000 lbs)",
       y = "Miles Per Gallon")
  
print(p)

# CUSTOMIZE THROUGH GGPLOT2 

p2 <- ggplot(mtcars, aes(x = wt, y = mpg, color = factor(cyl))) +
  geom_point(size = 3) +
  geom_smooth(method = "lm", se = FALSE) +
  labs(title = "MPG vs Weight by Cylinder Count",
       x = "Weight (1000 lbs)",
       y = "MPG",
       color = "Cylinders")

print(p2)

## `geom_smooth()` using formula = 'y ~ x'

# Change point color by a factor (cyl) #

# Add smoothing line (geom_smooth) #

# CONVERT GGPLOT2 PLOT TO INTERACTIVE PLOTLY PLOT

interactive_plot <- ggplotly(p2) %>%
  layout(title = "Interactive MPG vs Weight",
         xaxis = list(title = "Car Weight"),
         yaxis = list(title = "Miles Per Gallon"))

## `geom_smooth()` using formula = 'y ~ x'

interactive_plot

# USING PLOTLY WITHOUT GGPLOT2 

plot_ly(data = mtcars, x = ~wt, y = ~mpg, type = 'scatter', mode = 'markers',
        color = ~factor(cyl), marker = list(size = 10)) %>%
  layout(title = "Plotly Scatter Plot",
         xaxis = list(title = "Weight"),
         yaxis = list(title = "MPG"))

# SAVING THE PLOTS 

ggsave("myplot.png", p2, width = 6, height = 4)

## `geom_smooth()` using formula = 'y ~ x'

htmlwidgets::saveWidget(interactive_plot, "interactive_plot.html")

## Remember aesthetics (aes()) control mapping of variables. ##

## Layers are additive: + adds geoms, themes, labels. ##

## geom_point(), geom_line(), geom_smooth() are common geoms. ##

## ggplotly() converts static ggplot2 objects to interactive plotly objects. ##

## Use layout() in plotly to customize titles and axis labels after conversion.V ##